Showing papers on "Network traffic simulation published in 2005"

Dynamic Wavelet Neural Network Model for Traffic Flow Forecasting

Abstract: Accurate and timely forecasting of traffic flow is of paramount importance for effective management of traffic congestion in intelligent transportation systems. In this paper, a novel nonparametric dynamic time-delay recurrent wavelet neural network model is presented for forecasting traffic flow. The model incorporates the self-similar, singular, and fractal properties discovered in the traffic flow. The concept of wavelet frame is introduced and exploited in the model to provide flexibility in the design of wavelets and to add extra features such as adaptable translation parameters desirable in traffic flow forecasting. The statistical autocorrelation function is used for selection of the optimum input dimension of traffic flow time series. The model incorporates both the time of the day and the day of the week of the prediction time. As such, it can be used for long-term traffic flow forecasting in addition to short-term forecasting. The model has been validated using actual freeway traffic flow data. The model can assist traffic engineers and highway agencies to create effective traffic management plans for alleviating freeway congestions.

System and method of characterizing and managing electronic traffic

Abstract: A system and method for monitoring and dynamically managing all user traffic at point of log-in and throughout a user's network experience. Rules may be enforced based on observed traffic of users at and after log-in and up until log off. The system automatically detects network traffic and dynamically responds to potential attacks with extremely high speed and efficiency. Rich Traffic Analysis (RTA) offers greater network traffic characterization accuracy, detection speed, network management options and intrusion prevention capabilities. The system has ability to view all network traffic in the full context of users, applications, data and system access which offers strong, verifiable and accurate protection of networked assets. The system employs several traffic sensor devices communicating with a central manager device ena~ ing the high-speed characterization of each network packets traversing the network. This provides a more solid basis for legitimately taking action and enforcing rules on the observed traffic.

Routing of Uncertain Traffic Demands

Abstract: Due to the success of the Internet and the diversity of communication applications, it is becoming increasingly difficult to forecast traffic patterns. To capture the traffic variations, we introduce a flexible model where traffic belongs to a polytope. We assume that the traffic demands between nodes can be carried on many paths, with respect to network resources. Moreover, to guarantee the network stability and to make the routing easy to implement, the proportions of traffic flowing through each path have to be independent of the current traffic demands. We show that a minimum-cost routing satisfying the previous properties can be efficiently computed by column and constraint generations. We then present several strategies related to certain algorithmic details. Finally, theoretical and computational studies show that this new flexible model can be much more economical than a classical deterministic model based on a given traffic matrix. This paper can be considered as a mathematical framework for a new flexible virtual private network service offer. It also introduces a new concept: the routing of a polytope.

Network testing systems

Abstract: A method of testing a digital mobile phone network such as a GPRS or 3 G network comprises creating test traffic using an unmodified test mobile phone coupled to a computer, and using the computer to measure a parameter associated with the network's response to the test traffic. The measurements made by the computer are encoded into the test traffic to create a data stream within the mobile phone network comprising test traffic, measurements relating to the test traffic, and signalling relating to the test traffic, whereby this data stream can be captured at points within the network and analysed to investigate the functioning of the network dynamically as the network is exercised with the test traffic. Software and test equipment for performing the method are also described.

Study on network traffic prediction techniques

Abstract: We briefly describe a number of traffic predictors (such as ARIMA, FARIMA, ANN and wavelet-based predictors) and analyze their computational complexity. We compare their performance with MSE, NMSE and computational complexity by simulating the predictors on four wireless network traffic traces and decide the most suitable network traffic predictor based on acceptable performance and accuracy.

Flows based visualization of packet networks with network performance analysis, troubleshooting, optimization and network history backlog

Abstract: The present invention is a computer system and a method for gathering, processing and analysis of network information resulting in presentation and visualization of packet networks in the form of individual virtual flows, sometimes also called connections or sessions, containing their statistical characteristics in a time-sampled dynamics. The system, deployed as a separate device or co-hosted with other network devices, collects and processes information from all valid packets in network, classifies and maps gathered statistics to the statistics of relevant virtual flows. The statistical information is further processed by the system to provide near-real presentation, as well as stored in a searchable database for future analyses. The invention to be used by network engineers and administrators as a tool for a near real-time control of network traffic, as an analytical tool for solving network bottlenecks, network performance optimization and troubleshooting analyses, cutting costs by optimizing network layout, appropriate organization of traffic and intelligent configuration of QoS, routers and other network devices.

Simulation studies of information propagation in a self-organizing distributed traffic information system

Abstract: This paper investigates the feasibility of a self-organizing, completely distributed traffic information system based upon vehicle-to-vehicle communication technologies. Unlike centralized traffic information systems, the proposed system does not need public infrastructure investment as a prerequisite for implementation. Due to the complexity of the proposed system, simulation is selected as the primary approach in the feasibility studies. A simulation framework is built based on an existing microscopic traffic simulation model for the simulation studies. The critical questions for building the proposed market-driven system are examined both from communication requirements and traffic engineering points of view. Traffic information propagation both in freeway and arterial networks via information exchange among IVC-equipped vehicles is tested within the simulation framework. Results on the probability of successful IVC and traffic information propagation distance obtained from the simulation studies are generated and analyzed under incident-free and incident conditions for various roadway formats and parameter combinations. Comparisons between the speed of the incident information wave and the speed of the corresponding traffic shock wave due to the incident are analyzed for different scenarios as the most crucial aspect of the information propagation as a potential foundation for application in such a decentralized traffic information system.

Simulation of car-to-car messaging: analyzing the impact on road traffic

Abstract: In this paper we present a special simulation environment, used to analyze the effects of a real-time vehicle-to-vehicle warning-message distribution application on road traffic. For the realization of this environment, a coupling concept for coupling a traffic and a network simulator has been developed and implemented. Besides the simulation environment and its realization we'II present simulation results.

Application-Level Traffic Monitoring and an Analysis on IP Networks

Abstract: Traditional traffic identification methods based on wellknown port numbers are not appropriate for the identification of new types of Internet applications. This paper proposes a new method to identify current Internet traffic, which is a preliminary but essential step toward traffic characterization. We categorized most current network-based applications into several classes according to their traffic patterns. Then, using this categorization, we developed a flow grouping method that determines the application name of traffic flows. We have incorporated our method into NG-MON, a traffic analysis system, to analyze Internet traffic between our enterprise network and the Internet, and characterized all the traffic according to their application types.

Simulation of modern Traffic Lights Control Systems using the open source Traffic Simulation SUMO

Abstract: Within the project “OIS” (optical information systems) new traffic control mechanisms had to be invented and tested. One of the most important topics was to optimize the flow over a junction using information from the OIS sensors which can not be measured using normal sensors such as induct loops. For this purpose, an “agentbased” traffic lights logic algorithm was used, which uses the length of a jam in front of a traffic light as input. As we had no possibility to test the traffic lights control within the reality, the improvement of the flow throughput of such junctions was shown using the open source traffic Simulation “SUMO” (Simulation of Urban MObility) [1, 2]. This publication describes the algorithm itself and how it was embedded within the simulation. Furthermore, the simulation results are given.

A Network Traffic Generator Model for Fast Network-on-Chip Simulation

Abstract: For systems-on-chip (SoC) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast and effective network-on-chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns and resource contention in a system are dependent on the interconnect architecture, and our TG is designed to capture the resulting reactiveness. The regenerated traffic, which represents a realistic workload, can thus be used to undertake faster architectural exploration of interconnection alternatives, effectively decoupling simulation of IP cores and of interconnect fabrics. The results with the TG on an AMBA interconnect show a simulation time speedup above a factor of 2 over a complete system simulation, with close to 100 % accuracy.

Traffic flow forecasting using a spatio-temporal Bayesian network predictor

Abstract: A novel predictor for traffic flow forecasting, namely spatiotemporal Bayesian network predictor, is proposed. Unlike existing methods, our approach incorporates all the spatial and temporal information available in a transportation network to carry our traffic flow forecasting of the current site. The Pearson correlation coefficient is adopted to rank the input variables (traffic flows) for prediction, and the best-first strategy is employed to select a subset as the cause nodes of a Bayesian network. Given the derived cause nodes and the corresponding effect node in the spatio-temporal Bayesian network, a Gaussian Mixture Model is applied to describe the statistical relationship between the input and output. Finally, traffic flow forecasting is performed under the criterion of Minimum Mean Square Error (M.M.S.E.). Experimental results with the urban vehicular flow data of Beijing demonstrate the effectiveness of our presented spatio-temporal Bayesian network predictor.

Intersection Modeling, Application to Macroscopic Network Traffic Flow Models and Traffic Management

Abstract: The object of the paper is to analyze intersection modeling in the context of macroscopic traffic flow models. The paper begins with a brief review of classical boundary conditions of the Dubois-LeFloch and the Bardos-Nedelec-LeRoux type, and their relation to the concepts of local traffic supply and demand. It will be shown that the local traffic supply and demand concept extends and simplifies these classical approaches. The resulting constraints on phenomenological intersection models will be discussed. Several examples of intersection models are deduced. Some of these recapture earlier models; others are specifically designed for congested traffic conditions and take into account the bounds on car acceleration. The last part of the paper is devoted to network modeling and to applications to network traffic management.

Network simulation apparatus and method for analyzing abnormal network

Abstract: A network simulation apparatus and method for analyzing abnormal network traffic are provided. The network simulation apparatus includes: a traffic information collection unit, which collects traffic information in real time from a network; a simulator, which performs a simulation operation in a virtual network topology environment according to a predetermined scenario, the virtual network topology environment generating virtual traffic including a normal virtual packet modeled based on a normal traffic environment and an abnormal virtual packet modeled based on an abnormal traffic environment with a network traffic attack launched thereupon based on the collected real-time traffic information; and an interface unit, which provides the simulation operation results to a user. Accordingly, it is possible to effectively detect, analyze, and deal with abnormal network traffic that has occurred in a network to be managed.

A distributed, scalable, and synchronized framework for large-scale microscopic traffic simulation

Abstract: Microscopic traffic simulation is effective for analyzing transportation networks. However, performing microscopic simulations for large-scale networks remains a huge computing problem. In this paper, we present ParamGrid, a scalable and synchronized framework that distributes the simulation across a cluster of ordinary-performance, low-cost personal computers (PCs) connected by local area network (LAN). Several key challenges are solved: dividing a large traffic network, routing vehicles traveling across tiles, transferring vehicles across tiles, and globally synchronizing the simulation time to achieve a complete solution to automate scalable concurrent simulations. These solutions are automated in ParamGrid. Our experimental results, using a real-world traffic network for the Long Beach Area in Southern California, show our new framework provides near linear speed-up with number of computers.

Integrated network experimentation using simulation and emulation

Abstract: Discrete-event packet-level network simulation is well-known and widely used. Network emulation is a hybrid approach that combines real elements of a deployed networked application-such as end hosts and protocol implementations-with synthetic, simulated, or abstracted elements-such as the network links, intermediate nodes and background traffic. A key difference between the two approaches is that in the former, the notion of time is virtual and is independent of real time, whereas the latter must execute in real time. Emulation gains realism while naturally foregoing complete repeatability; historically, emulation was also tedious to control and manage. We define integrated network experimentation as spatially combining real elements with simulated elements in the same experimental run, each modeling different portions of a network topology. Integrated experiments enable new validation techniques and larger experiments than obtainable by using real elements alone. This paper highlights the key issues in integrated network experimentation and presents some of the design techniques we use in designing, building, and putting into public production use such an integrated environment, running on a space-shared cluster.

System and method for monitoring network traffic

Abstract: Described is a method of assigning a network address to a trap, the network address being a dark address of a virtual private network. The network traffic destined for the network address is monitored and a classification of the network traffic is determined. After the classification, a predetermined response is executed based on the classification of the traffic.

Traffic generation and performance evaluation for mesh-based NoCs

Abstract: The designer of a system on a chip (SoC) that connects IP cores through a network on chip (NoC) needs methods to support application performance evaluation. Two key aspects these methods have to address are the generation and evaluation of network traffic. Traffic generation allows injecting packets in the network according to application constraint specifications such as transmission rate and end-to-end latency. Performance evaluation helps in computing latency and throughput at network channels/interfaces, as well as to identify congestion and hot-spots. This paper reviews related works in traffic generation and performance evaluation for mesh topology NoCs, and proposes general methods for both aspects. Three parameters are used here to define traffic generation: packet spatial distribution, packet injection rate and packet size. Two types of methods to evaluate performance in NoCs are discussed: (i) external evaluation, a common strategy found in related works, where the network is considered as a black box and traffic results are obtained only from the external network interfaces; (ii) internal evaluation, where performance is computed in each network channel. The paper presents the result of experiments conducted in an 8times8 mesh network, varying the routing algorithms and the number of virtual channels. The main contribution of this work is the set of methods for internal NoC evaluation, which help designers to optimize the network under different traffic scenarios

Short-Term Traffic Forecasting in a Campus-Wide Wireless Network

Abstract: Our goal is to characterize the traffic load in an IEEE802.11 infrastructure. This can be beneficial in many domains, including coverage planning, resource reservation, network monitoring for anomaly detection, and producing more accurate simulation models. The key issue that drives this study is traffic forecasting at each wireless access point (AP) in an hourly timescale. We conducted an extensive measurement study of wireless users on a major university campus using the IEEE802.11 wireless infrastructure. We propose several traffic models that take into account the periodicity and recent traffic history for each AP and present a time-series forecasting methodology. Finally, we build and evaluate these forecasting algorithms and discuss our findings

Dynamic road pricing for optimizing network performance with heterogeneous users

Abstract: In transport networks, travelers individually make route and departure time choice decisions that may not be optimal for the whole network. By introducing (time-dependent) tolls the network performance may be optimized. In the paper, the effects of time-dependent tolls on the network performance are analyzed using a dynamic traffic model. The network design problem is formulated as a bi-level optimization problem in which the upper level describes the network performance with chosen toll levels while the lower level describes the dynamic network model including user-specific route and departure time choice and the dynamic network loading. In case studies on a simple hypothetical network it is shown that network improvements can be obtained by introducing tolls. It is also shown that finding a global solution to the network design problem is complex as it is non-linear and non-convex.

Intelligent cooperation control of urban traffic networks

Abstract: Area-wide traffic control in urban areas is complicated. Traffic conditions are often changeable and random. This paper develops and tests a distributed system of urban traffic control, for use within traffic signal controlled networks. The system uses multi-agent and information fusion technology. The system framework and agent structure are discussed in the paper. The intelligent cooperation algorithm used by the proposed urban traffic control system is based on genetic reinforcement learning. The system is capable of responding to changing traffic conditions in real-time. It has the ability to coordinate and optimize the traffic signal controlled network through system self-study and adaptability. The validity of the algorithm is tested using simulation analysis.

Methods, systems, and computer program products for modeling and simulating application-level traffic characteristics in a network based on transport and network layer header information

Abstract: Methods, systems, and computer program products are disclosed for determining application-level traffic characteristics in a network based on transport and network layer header information. Transport and network layer header information is collected from packet traffic in a network. Packets are classified to different connections based on the transport and network layer header information. Each connection is modeled using an abstract syntax for characterizing bidirectional interactions between endpoints of each connection and delays between the interactions. The bidirectional interactions include data-concurrent interactions. Application-level characteristics of the packet traffic are determined based on the modeled connections. Simulated traffic that models application-level traffic behavior in a real network may also be generated by simulating traffic connections based on the modeled connections.

Finding critical traffic matrices

Abstract: A traffic matrix represents the amount of traffic between origin and destination in a network. It has tremendous potential utility for many IP network engineering applications, such as network survivability analysis, traffic engineering, and capacity planning. Recent advances in traffic matrix estimation have enabled ISPs to measure traffic matrices continuously. Yet a major challenge remains towards achieving the full potential of traffic matrices. In practical networking applications, it is often inconvenient (if not infeasible) to deal with hundreds or thousands of measured traffic matrices. So it is highly desirable to be able to extract a small number of "critical" traffic matrices. Unfortunately, we are not aware of any good existing solutions to this problem (other than a few ad hoc heuristics). This seriously limits the applicability of traffic matrices. To bridge the gap between the measurement and the actual application of traffic matrices, we study the critical traffic matrices selection (CritMat) problem in this paper. We developed a mathematical problem formalization after identifying the key requirements and properties of CritMat in the context of network design and analysis. Our complexity analysis showed that CritMat is NP-hard. We then developed several clustering-based approximation algorithms to CritMat. We evaluated these algorithms using a large collection of real traffic matrices collected in AT&T's North American backbone network. Our results demonstrated that these algorithms are very effective and that a small number (e.g., 12) of critical traffic matrices suffice to yield satisfactory performance.

KUTE A high performance Kernel-based UDP traffic engine

Abstract: Numerous tools have been developed for generating artificial traffic flows. These traffic generators are commonly used for emulating applications, measuring various network characteristics, or just generating traffic for performance tests. The performance of many applications, such as packet measurement tools, heavily depends on the packet rate of the network traffic under observation. The existing traffic generators are mostly user space implementations, which limits their performance, especially in high-speed networks such as Gigabit Ethernet. In this paper we present and evaluate KUTE, a UDP packet generator and receiver which runs entirely in the Linux kernel. We compare KUTE with a similar user space tool named RUDE/CRUDE and find that KUTE is able to send and receive much higher packet rates, produces more accurate interpacket gaps at the sender, and more accurately measures interarrival times at the receiver.

Optimization of Highway Networks and Traffic Forecasting

Abstract: The understanding of traffic dynamics on highway networks is essential for traffic control. Nowadays realistic microscopic models exist that allow highly efficient (faster-than-real-time) simulations of large networks. These simulations can be used not only to determine the state of the network from incomplete information, but also for traffic forecasting. We also discuss an analysis of the highway network in Germany to identify bottlenecks and possible optimization strategies. Language: en

A Dynamic Network Simulation Model Based on Multi-Agent Systems

Abstract: This paper reports on how the abstraction approach of multi-agent systems can be used to represent the complexity inherent in the urban traffic domain, accounting for the importance of modelling travellers’ behaviour and their interaction with intelligent transportation technologies. A key premise in the approach proposed is the identification of what we have coined autonomous decision entity, which is defined as an agent shell to structure the way agents can be implemented and inserted into the environment. Such a structure is very flexible in the sense it is only defined in meta-level, comprising sensors, effectors and a reasoning kernel. The conceptual multi-agent model is presented and implemented within the DRACULA simulation suite, which is used for simulation experiments on the analysis of drivers’ route and departure time choice.

Advanced concepts in large-scale network simulation

Abstract: This tutorial paper reviews existing concepts and future directions in selected areas related to simulation of large scale networks. It covers specifically topics in traffic modeling, simulation of routing, network emulation, and real time simulation.

Characterising Distributed Haptic Virtual Environment Network Traffic Flows

Abstract: The effective transmission of haptic data in Distributed Haptic Virtual Environment (DHVEs) is a new research area which presents a number of challenges to the underlying network. The transmission of reflected force in these applications has the potential to change the way humans interact with machines and communicate with each other. The future Internet will have to carry multiple DHVE type traffic and it is now established that the best effort service offered by current IP networks is insufficient to meet the needs of these type of applications, which require specific Quality of Service (QoS) from network. The aim of the work presented here is to characterise the traffic generated by multiple DHVE network connections. The approach taken is to develop a simulation model of DHVE traffic based on empirical measurements. Both synchronous and asynchronous real world DHVE traffic is analyzed, quantified and imported into a network simulation. Probability Density Function (PDF) models are subsequently derived for each type of traffic in the DHVE system. The results show the network simulation model compares favourably with the physical network, and can be used to generate a scalable haptic network model where multiple DHVE connections may be examined.

Tracking of traffic engineering topology in an autonomous system

Abstract: A network topology map and a system and method of annotating a network topology map of a packet network is described which monitors traffic engineering extensions in link state advertisement packets. Traffic engineering information contained in traffic engineering extensions is extracted and the traffic engineering information is used to annotate the network topology map with network attributes, such as bandwidth information and traffic engineering metrics.